Bibliographic record
Abstract
Purpose – This paper aims to report on the level of entrepreneurial intent (EI) in southwestern Cameroon, by developing and using a novel scale that avoids the problems of construct confounds that exist with most EI scales currently in the literature. This scale is also used to measure EI in Canada, as a comparative example of the Western countries typical of previous EI research, to demonstrate the stability of the scale across different cultures. Design/methodology/approach – Data are collected by survey of random participants in Jamaica and Canada. Factor analysis is used to refine the choice of scale elements from this survey. Nested structural equation modelling is then used to confirm the construct validity and to demonstrate construct stability across the two populations. The population scores are then compared byt-test. Findings – A novel ten-item scale is developed and is shown to have a stable factor structure across the two populations. Using this measure, it can be newly seen that, contrary to the expectations for low entrepreneurial prevalence and intention expressed in the literature, there is actually no significant EI deficit in Cameroon. Research limitations/implications – Previous measures of EI in the literature have been seriously confounded by adjacent constructs in the same nomological net, such as beliefs, attitudes and expectations for future behaviours. The research approach taken here demonstrates how these confounds may have led to erroneous conclusions about EI in Cameroon and potentially in other countries. The major limitation of this study is the small sample size, which should be reinforced by replication or extension in future studies. Originality/value – The development of a scale free of construct confounds represents an important step in the refinement of accurate measurement of this foundational construct in entrepreneurship research. This is underscored by the finding that EI in Cameroon may have been misreported in early research due to confounded measurement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".